835 words - 4 pages

Linear algebra is a useful tool with many applications within the computer science field. This paper will cover the various applications of linear algebra in computer science including: internet search, graphics, speech recognition,and artificial intelligence. A major focus of linear algebra in computer science is internet searches, which involves finding techniques for effectively storing and searching through information.

In the year 2000 there was an estimated 2.5 billion web pages on the internet, with a growth rate of 7.3 million per day. Linear algebra is used in the organization and sorting of these web pages when storing them in an internet search database. The vector space model;is ...view middle of the document...

Linear algebra is equally helpful in improving graphics within the field of computer science.

Linear algebra is used in computer graphics to manipulate the way in which an object

may be translated, scaled, and rotated. Translation, or the ability to move an object to a different place on the screen, can be done by adding two vectors together. Scaling, or increasing or decreasing the size of an object on the screen, can be represented by matrix multiplication where the scaling is done along the diagonal factors. The rotation of an object among a pivot point can also be done by matrix multiplication. The use of linear algebra in computer graphics has declined due to the lack of need to manipulate objects to the proper screen size since the improvement of displays. Linear algebra is still used in the mobile graphics portion of computer science since phones have relatively smaller sized screens. Voice recognition which is a focus of mobile applications used on cellphones also incorporates linear algebra.

Voice recognition is based on the principle that clean signal can be confined within a noisy Euclidean space. Decomposing the vector space of the noisy signal into two separate subspaces: one that is occupied by the clean signal and one that is occupied by the noise signal, allows us to estimate the clean signal. There are several methods that were proposed based on singular value decomposition or eigenvalue decomposition. This is used to enhance the speech and to make it easier to understand by...

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